Hyunjo Lee

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Travel time prediction is an indispensable for numerous intelligent transportation systems (ITS) including advanced traveler information systems. The main purpose of this research is to develop a dynamic travel time prediction model for road networks. In this study we proposed a new method to predict travel times using Artificial Neural Network model(More)
Recent development in wireless communication technology and mobile equipment like PDA, cellular phone and GPS is making location-based services (LBSs) more popular day by day. However, because, in the LBSs, users continuously send queries to LBS servers by using their exact locations, private information could be in danger. Therefore, a mechanism for users'(More)
Prediction of travel time has major concern in the research domain of Intelligent Transportation Systems (ITS). Clustering strategy can be used as a powerful tool of discovering hidden knowledge that can easily be applied on historical traffic data to predict accurate travel time. In our Modified K-means Clustering (MKC) approach, a set of historical data(More)